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Sr. Applied Scientist, Alexa Smart Home

Job in Vancouver, BC, Canada
Listing for: Amazon
Full Time position
Listed on 2026-09-14
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 196000 - 327000 CAD Yearly CAD 196000.00 327000.00 YEAR
Job Description & How to Apply Below

Description

Alexa Smart Home Science builds the intelligence that lets customers control and automate their homes naturally, spanning voice understanding, proactive automation, habit and preference learning, and the LLM/agentic systems that power the next generation of ambient home experiences. We are looking for a Senior Applied Scientist to own the scientific direction of a major workstream, turning ambiguous, open-ended problems into production systems that measurably improve the customer experience across millions of homes.

Description

Alexa Smart Home Science builds the intelligence that lets customers control and automate their homes naturally, spanning voice understanding, proactive automation, habit and preference learning, and the LLM/agentic systems that power the next generation of ambient home experiences. We are looking for a Senior Applied Scientist to own the scientific direction of a major workstream, turning ambiguous, open-ended problems into production systems that measurably improve the customer experience across millions of homes.

You will define the research agenda for your area, partner deeply with engineering to bring models into production, and raise the scientific bar across the broader team. You will work at the intersection of large language models, agentic orchestration, personalization, and real-world heterogeneity across homes, devices, and occupants. This is a hands‑on role: you will frame the problems, build the models, guide the system design, and mentor other scientists, while influencing product and technical roadmaps beyond your immediate team.

Key job responsibilities

  • Independently identify, frame, and solve ill‑defined research problems tied to broad Smart Home problem areas, delivering with limited guidance.
  • Define system‑level technical requirements and partner with engineering teams to adapt scientific techniques to meet production constraints (latency, cost, reliability), making appropriate tradeoffs.
  • Own the science strategy and roadmap for a workstream; anticipate future business and technical requirements.
  • Design and run rigorous experimentation and evaluation to validate approaches and quantify customer/business impact.
  • Build consensus on scientific approach and best practices across multiple teams; influence product features and technical direction beyond your own team.
  • Actively mentor and develop other scientists, and raise the bar in hiring.
  • Contribute to the internal and external scientific community through publications, patents, and dissemination of scientific artifacts.

A day in the life

No two days look alike, but the through line is owning a scientific problem from question to production impact. You might dig into evaluation results to find where the experience falls short, frame a hypothesis, and prototype with LLMs or agentic techniques. You will pair with engineering to turn a promising model into a production‑ready design, weighing latency, cost, and reliability tradeoffs.

Expect alignment with product managers on customer problems, working sessions with fellow scientists, and time mentoring teammates. Your customers are Alexa smart home users across millions of households; your stakeholders span product, engineering, and partner science teams.

About The Team

We are the science team behind Alexa's smart home experience. We are applied scientists and science engineers making the home genuinely intelligent: anticipatory, personalized, and effortless. Our mission is to move Alexa from reacting to commands toward understanding a household's rhythms and acting helpfully on the customer's behalf, reliably and ause no two homes are alike, we embrace that diversity rather than paper over it.

We value research‑grounded decisions, hands‑on work,…

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